AFAAN OROMOO NEWS CLASSIFICATION SYSTEM

Overview

AFAAN OROMOO NEWS CLASSIFICATION SYSTEM is a machine learning project designed to classify news articles written in Afaan Oromoo, the Oromo language. The primary goal of this project is to leverage natural language processing (NLP) techniques to automatically categorize news content into various predefined categories.

Key Features

Language Support: Afaan Oromoo is a widely spoken language, and this project aims to enhance accessibility to news articles in this language.
Multiclass Classification: The system is capable of classifying news articles into multiple categories, providing a comprehensive understanding of the content.
Rule-Based Stemmer: The project incorporates a rule-based stemmer based on the hybrid approach described in the paper "Designing a Stemmer for Afaan Oromo Text: A Hybrid Approach" by Debela Tesfaye.

Purpose

The motivation behind this project is to contribute to the enhancement of information accessibility for Afaan Oromoo speakers. By automating the categorization of news articles, individuals can easily navigate through relevant content based on their interests.

Target Audience

This project is intended for individuals interested in Afaan Oromoo language and those seeking to implement or understand machine learning techniques for natural language processing.

Project Structure

The project is organized into distinct directories, each serving a specific purpose.
📦 afaan-oromoo-news-classification-system
┣ 📂api
┃ ┣ 📜app.py
┃ ┣ 📜model_loader.py
┣ 📂data
┣ 📂docs
┃ ┣ 📜model_documentation.pdf
┣ 📂logs
┣ 📂models
┃ ┣ 📂trained_models
┃ ┃ ┣ 📜label_encoder.joblib
┃ ┃ ┣ 📜model_20231116_accuracy_0.9263.h5
┃ ┃ ┗ 📜tokenizer.joblib
┃ ┣ 📜train_model.ipynb
┣ 📂preprocessing
┃ ┣ 📜preprocessing_pipeline.py
┃ ┣ 📜special_character_handler.py
┃ ┣ 📜stemmer.py
┃ ┣ 📜stopword_remover.py
┃ ┣ 📜tokenizer.py
┣ 📂scrapers
┃ ┣ 📜fbc_scraper.py
┣ 📂tests
┃ ┣ 📜test_preprocessing.py
┗ 📜requirements.txt

This structure helps maintain code separation and modularity. Key folders include api for the Flask API, preprocessing for text processing modules, docs for documentations, models for training and storing trained models, scrappers for web scrapping scripts and tests for unit tests.

Getting Started

To set up the project locally, follow these steps:

Clone the Repository:

git clone https://github.com/abdulmunimjemal/afaan-oromoo-news-classification-system.git
cd afaan-oromoo-news-classification-system

Install Dependencies:

   pip install -r requirements.txt

Clone the Repository:
```
 cd api
 python app.py
```
The API should now be accessible at http://localhost:5000/predict/.

Test the API:

curl -X POST -H "Content-Type: application/json" -d '{"text": "Your sample afaan oromootext here."}' http://localhost:5000/predict

Adjust the payload and URL based on your API endpoints. Now, the project should be set up locally, and you can begin exploring and using the features.

Dependencies

The project relies on the following external dependencies:
- Pandas: A powerful data manipulation and analysis library for working with structured data.
- Flask: A lightweight web application framework for the API.
- scikit-learn: A machine learning library for model training and evaluation.
- TensorFlow: An open-source machine learning framework used for building and training neural networks.

Make sure to install these dependencies using the provided requirements.txt file:

pip install -r requirements.txt

Contributing

We welcome contributions from the community. If you'd like to contribute, please follow these steps:

Fork the repository
Create a new branch (git checkout -b feature/your-feature)
Make your changes
Commit your changes (git commit -m 'Add your feature')
Push to the branch (git push origin feature/your-feature)
Open a pull request

License

This project is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit here or see the LICENSE.md file.

License Summary: This project is intended for educational and non-commercial purposes only. Users are required to provide proper attribution to the authors and share any derivative works under the same license terms.

Authors

Abdulmunim Jundurahman

Contributors

Ishak Sebsib

FAQ

Q: Can I use this project for commercial purposes?

A: No, this project is intended for educational purposes only.

Q: How do I cite this project?

A: When using this project, please provide proper attribution to the authors.

ishaksebsib/afaan-oromoo-news-classification-system